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Journal : Jupiter

Perancangan Arsitektur Enterprise Pada Yayasan Pembangunan Pondok Pesantren Bustanul Ulum Menggunakan Framework Gartner Irawan, Asep; Widi Nugroho, Handoyo; Purnomo, Hendri
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.11540490

Abstract

This study focuses on the design of an information system architecture at Yayasan Pembangunan Pondok Pesantren Bustanul 'Ulum using the Gartner Enterprise Architecture model. The main objective of this design is to develop and implement information technology that can enhance the efficiency and effectiveness of business processes and administrative management at the foundation. The design stages include analyzing environmental trends and business strategies, developing requirements, principles, and architectural models, as well as designing a future architecture that encompasses business, information, and technology architecture. The analysis results indicate an urgent need to upgrade IT facilities, develop documentation and authentication systems, and integrate the laboratory system. The implementation of this architecture is expected to support the foundation's goals in providing quality education and improving school management performance.  
JURNAL ASSESSMENT OF INFORMATION TECHNOLOGY GOVERNANCE USING COBIT 2019 FRAMEWORK (CASE STUDY OF NATAR MEDIKA HOSPITAL): PENILAIAN TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN FRAMEWORK COBIT 2019 (STUDI KASUS RS NATAR MEDIKA) Satria Kusuma, Lutvianus; Wasilah, Wasilah; Purnomo, Hendri
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12577212

Abstract

This study evaluates the maturity level of various domains within the COBIT framework in an organization, as well as identifies the gap between current performance and expected performance. The collected data indicates significant differences in maturity levels for domains APO.07, DSS02, DSS.03, DSS.04, DSS.05, and MEA.01, with an average gap of 2.11. Based on these findings, various actions are recommended to improve maturity levels, including increased training and development, adoption of process automation, periodic assessments, improved monitoring and reporting, and more effective risk management. Implementation of these recommendations is expected to reduce the existing gap and enhance overall operational efficiency. Keywords: COBIT, Maturity Level, GAP Analysis, APO.07, DSS02, DSS.03, DSS.04, DSS.05, MEA.01
teknika DATA MINING TO PREDICTE STUDENT ACHIEVEMENT BASED ON SOCIO-ECONOMIC, MOTIVATION, DISCIPLINE AND PAST ACHIEVEMENT AT VOCATIONAL SCHOOL 1 PENAWARTAMA TULBABAG USING THE C4.5 ALGORITHM: DATA MINING UNTUK MEMPREDIKSI PRESTASI PESERTA DIDIK BERDASARKAN SOSIAL EKONOMI, MOTIVASI, KEDISIPLINAN DAN PRESTASI MASA LALU DI SMKN 1 PENAWARTAMA TULANG BAWANG MENGGUNAKAN ALGORITMA C4.5 Suroto, Suroto; Purnomo, Hendri; Estian Pambudi, Randi
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 16 No 2 (2024): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.12743856

Abstract

SMK Negeri 1 Penawartama Tulang Bawang is a school whose students come from various villages in the district. Most of the students come from families with limited economic conditions and low levels of education. These factors often affect the students' learning motivation. The aim of this research is to predict students' academic performance based on parents' socioeconomic status, motivation level, discipline level, and previous academic achievements using data mining methods with the C4.5 algorithm. This research employs a quantitative approach involving 606 tenth-grade students at SMK Negeri 1 Penawartama Tulang Bawang. Data collection methods used include documentation and questionnaires. The research results show that the prediction analysis using decision trees has an accuracy rate of 98.02%, precision of 94.44%, and recall of 77.27%.   Keywords: data mining, C4.5 algorithm, accuracy, precision, and recall
Klasifikasi Sentimen Ulasan Pengguna MyPertamina Menggunakan Algoritma Naive Bayes dan TF-IDF: Klasifikasi Sentimen Ulasan Pengguna MyPertamina Menggunakan Algoritma Naive Bayes dan TF-IDF Zulkarnaini, Zulkarnaini; Purnomo, Hendri; Firdhayanti, Ayu
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 17 No 2 (2025): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Analisis sentimen merupakan cabang dari pemrosesan bahasa alami (Natural Language Processing) yang berfungsi untuk mengevaluasi opini atau emosi pengguna terhadap suatu objek berdasarkan teks. Penelitian ini bertujuan untuk mengklasifikasikan sentimen ulasan pengguna terhadap aplikasi MyPertamina ke dalam tiga kategori, yaitu positif, netral, dan negatif. Data diperoleh dari ulasan pengguna aplikasi yang kemudian diolah melalui tahapan praproses teks dan vektorisasi menggunakan metode Term Frequency-Inverse Document Frequency (TF-IDF). Model klasifikasi yang digunakan dalam penelitian ini adalah Multinomial Naive Bayes karena kemampuannya dalam mengelola data teks yang bersifat multinomial. Hasil evaluasi menunjukkan bahwa algoritma Naive Bayes memberikan performa yang cukup baik dengan tingkat akurasi sebesar 84%. Selain itu, visualisasi WordCloud digunakan untuk menampilkan kata-kata yang paling sering muncul dalam tiap kategori sentimen, yang memberikan gambaran lebih mendalam mengenai persepsi pengguna. Penelitian ini menunjukkan bahwa analisis sentimen dapat menjadi alat bantu yang efektif dalam mengukur kepuasan pengguna serta dalam merumuskan strategi peningkatan kualitas layanan digital berbasis data.